code: def predict(self, word, pos=None):
      if pos is None:
          candidates = []
          if word not in self.dict:
              return candidates
  
          for pos in self.dict[word]:
              for candidate in self.dict[word][pos]:
                  candidates.append(candidate["synonym"])
  
          return candidates
  
      if word in self.dict and pos in self.dict[word]:
          return [
              candidate["synonym"] for candidate in self.dict[word][pos]
          ]
  
      return []
  
file_path: nlpaug/nlpaug/model/word_dict/ppdb.py
imports: from nlpaug.util import PartOfSpeech
  from nlpaug.model.word_dict import WordDictionary
label_desc: Use image node_id 5 for calling the Ppdb obj's underlying member method code with example usage: obj.predict(word, pos) and returns: list, candidates, unknown, candidates